The 2019 Michigan Student Symposium for Interdisciplinary Statistical Sciences
Thursday, March 28 – Friday, March 29, 2019
The Michigan Student Symposium for Interdisciplinary Statistical Sciences (MSSISS) is an annual event organized by graduate students in the Biostatistics, Electrical Engineering & Computer Science, Industrial & Operations Engineering, Statistics and Survey Methodology departments at the University of Michigan.
The goal of this symposium is to create an environment that allows communication across related fields of statistical sciences and promotes interdisciplinary research among graduate students and faculty. It encourages graduate students to present their work, share insights and exposes them to diverse applications of statistical sciences. Though hosted by five departments we extend our invitation to graduate students from all departments across the University to present their statistical research in the form of an oral paper presentation or a poster presentation. It also provides an excellent environment for interacting with students and faculty from other areas of statistical research on campus.
MSSISS is an opportunity for interdisciplinary research and discussion across the fields of statistical sciences. Calling all graduate students (as well as talented undergraduates)! Come along, present your work, share insights and learn about the diverse applications of statistical sciences.
Keynote Speakers of MSSISS 2019:
This year, we are fortunate to have Professor Alan E. Gelfand from Duke University as the keynote speaker, and Assistant Professor Ceren Budak from University of Michigan as the junior keynote speaker.
Michigan Junior Faculty Keynote: Ceren Budak
MSSISS 2019 Presentation Awards:
Best Oral Presentation:
Fernanda Alvarado-Leiton (Survey Methodology) – Effects of statistical adjustments for subgroup differences in non-probability sample web surveys
Oral Presentation Honorable Mention:
Elizabeth Hou (EECS) – Anomaly Detection in Partially Observed Traffic Networks
Best Speed Session:
Yutong Wang (EECS) – Unsupervised feature selection for manifold alignment of scRNA-seq data
ASA Prize for Best Poster Presentation:
Kevin Liao (Biostatistics) – The Effect of Mutation Subtypes on the Allele Frequency Spectrum and Population Genetics Inference
Departmental Poster Presentation Winners:
- Sunyi Chi (Biostatistics) – Prediction for an individual’s risk of PsA before symptoms appear using genetic data
- Alexander Ritchie (EECS) – Supervised Principal Component Analysis via Manifold Optimization
- Roger Fan (Statistics) – Precision Matrix Estimation with Noisy and Missing Data
- Micha Fischer (Survey Methodology) – Automated Model Selection within Sequential Imputation of Missing Data for High-Dimensional Data Sets